Follow this docs to install conda.

Then create a virtual environment.

$ conda create -n RKLLM-Toolkit python=3.8
$ conda activate RKLLM-Toolkit     #activate
$ conda deactivate                 #deactivate

Download Tool from airockchip/rknn-llm.

$ git clone https://github.com/airockchip/rknn-llm.git

$ cd rknn-llm/rkllm-toolkit/packages
$ pip3 install rkllm_toolkit-1.0.0-cp38-cp38-linux_x86_64.whl

Check whether install successfully.

$ python
$ from rkllm.api import RKLLM

Download Qwen-1.8B-Chat model in rknn-llm/rkllm-toolkit/examples/huggingface

$ cd rknn-llm/rkllm-toolkit/examples/huggingface
$ git lfs install
$ git clone https://huggingface.co/Qwen/Qwen-1_8B-Chat

Modify test.py as follows.

diff --git a/rkllm-toolkit/examples/huggingface/test.py b/rkllm-toolkit/examples/huggingface/test.py
index c253fe4..406ad37 100644
--- a/rkllm-toolkit/examples/huggingface/test.py
+++ b/rkllm-toolkit/examples/huggingface/test.py
@@ -5,7 +5,7 @@ https://huggingface.co/Qwen/Qwen-1_8B-Chat
 Download the Qwen model from the above website.
 '''
 
-modelpath = '/path/to/your/model'
+modelpath = './Qwen-1_8B-Chat'
 llm = RKLLM()
 
 # Load model

Run test.py to generate rkllm model.

$ python test.py

Model qwen.rkllm will generate in knn-llm/rkllm-toolkit/examples/huggingface.

The code is rknn-llm/rkllm-runtime. You can git clone again on Edge2 or copy from PC. Then pull qwen.rkllm in rknn-llm/rkllm-runtime/example.

Modify rknn-llm/rkllm-runtime/example/build-linux.sh as follows.

diff --git a/rkllm-runtime/example/build-linux.sh b/rkllm-runtime/example/build-linux.sh
index 712b3be..bc5c575 100644
--- a/rkllm-runtime/example/build-linux.sh
+++ b/rkllm-runtime/example/build-linux.sh
@@ -4,7 +4,7 @@ if [[ -z ${BUILD_TYPE} ]];then
     BUILD_TYPE=Release
 fi
 
-GCC_COMPILER_PATH=~/gcc-arm-10.2-2020.11-x86_64-aarch64-none-linux-gnu/bin/aarch64-none-linux-gnu
+GCC_COMPILER_PATH=aarch64-linux-gnu
 C_COMPILER=${GCC_COMPILER_PATH}-gcc
 CXX_COMPILER=${GCC_COMPILER_PATH}-g++
 STRIP_COMPILER=${GCC_COMPILER_PATH}-strip

$ cd rknn-llm/rkllm-runtime/example
$ bash build-linux.sh
$ export LD_LIBRARY_PATH=/home/khadas/rkllm-runtime/runtime/Linux/librkllm_api/aarch64/librkllmrt.so
$ cd build/build_linux_aarch64_Release
$ ulimit -n 10240
$ ./llm_demo ../../qwen.rkllm